AutoML Leaderboard

Best model name model_type metric_type metric_value train_time single_prediction_time
1_Linear Linear average_precision 0.981151 37.12 0.0285
2_Default_LightGBM LightGBM average_precision 0.984335 33.85 0.0133
3_Default_Xgboost Xgboost average_precision 0.979549 33.35 0.0228
4_Default_CatBoost CatBoost average_precision 0.987349 34.17 0.0333
5_Default_NeuralNetwork Neural Network average_precision 0.971355 32.2 0.0405
6_Default_RandomForest Random Forest average_precision 0.978456 35.77 0.1487
11_LightGBM LightGBM average_precision 0.984562 34.78 0.0148
7_Xgboost Xgboost average_precision 0.981538 35.11 0.0137
15_CatBoost CatBoost average_precision 0.988065 35.58 0.0174
19_RandomForest Random Forest average_precision 0.987365 38.27 0.1872
23_NeuralNetwork Neural Network average_precision 0.978522 32.79 0.0313
12_LightGBM LightGBM average_precision 0.981605 34.55 0.0182
8_Xgboost Xgboost average_precision 0.979431 33.48 0.0192
16_CatBoost CatBoost average_precision 0.981597 36.16 0.0246
20_RandomForest Random Forest average_precision 0.984126 37.24 0.1341
24_NeuralNetwork Neural Network average_precision 0.976907 34.78 0.037
13_LightGBM LightGBM average_precision 0.985243 35.9 0.0128
9_Xgboost Xgboost average_precision 0.911635 34.94 0.0144
17_CatBoost CatBoost average_precision 0.980034 36.34 0.0179
21_RandomForest Random Forest average_precision 0.968446 39.55 0.1381
25_NeuralNetwork Neural Network average_precision 0.969369 34.73 0.0367
14_LightGBM LightGBM average_precision 0.982671 36.43 0.0127
10_Xgboost Xgboost average_precision 0.500365 33.86 0.0145
18_CatBoost CatBoost average_precision 0.985217 36.49 0.0169
22_RandomForest Random Forest average_precision 0.973307 38.21 0.1672
26_NeuralNetwork Neural Network average_precision 0.97895 34.08 0.0343
15_CatBoost_GoldenFeatures CatBoost average_precision 0.987348 39.45 0.0404
19_RandomForest_GoldenFeatures Random Forest average_precision 0.981939 40.23 0.1546
4_Default_CatBoost_GoldenFeatures CatBoost average_precision 0.989526 37.73 0.0374
27_CatBoost_GoldenFeatures CatBoost average_precision 0.99044 37.09 0.0348
28_CatBoost CatBoost average_precision 0.97874 37.51 0.013
29_CatBoost CatBoost average_precision 0.990262 38.18 0.0183
30_RandomForest Random Forest average_precision 0.986077 40.24 0.1715
31_RandomForest Random Forest average_precision 0.985326 40.35 0.1417
32_LightGBM LightGBM average_precision 0.985875 37.62 0.0113
33_LightGBM LightGBM average_precision 0.984718 37.79 0.0159
34_LightGBM LightGBM average_precision 0.9859 37.05 0.0113
35_CatBoost_GoldenFeatures CatBoost average_precision 0.989239 38.26 0.0364
36_CatBoost_GoldenFeatures CatBoost average_precision 0.986614 39.03 0.0388
37_CatBoost CatBoost average_precision 0.985173 38.25 0.0144
38_CatBoost CatBoost average_precision 0.981361 39.14 0.0157
the best Ensemble Ensemble average_precision 0.992985 2.69 0.1873

AutoML Performance

AutoML Performance

AutoML Performance Boxplot

AutoML Performance Boxplot

Features Importance

features importance across models

Spearman Correlation of Models

models spearman correlation